Do the math: Best practices for pulmonary nodule management

 
 
 
 - lung
 

Out of a range of mathematical methods for managing pulmonary nodules with FDG PET/CT, one quantitative CT technique takes the lead--dynamic area-detector CT analyzed using the dual-input maximum slope method, according to a study published May 22 in the American Journal of Roentgenology .

Yoshiharu Ohno, MD, PhD, associate professor of radiology in the division of functional and diagnostic imaging research, Kobe University Graduate School of Medicine, in Hyogo, Japan, and colleagues employed dynamic area-detector CT while performing FDG PET/CT and compared quantitative analyses to see which was best suited to find patients’ pulmonary nodules.

“The diagnosis and management of pulmonary nodules in routine clinical practice is among the most common and most important areas of pulmonary medicine because they are caused by a variety of conditions, ranging from benign granulomas to operable primary malignant lung nodules,” wrote the authors. “In addition, the National Lung Screening Trial and previous screening trials have shown that low-dose lung CT is superior to chest radiography for the detection of pulmonary nodules and has potential to lower the risk of dying of lung cancer. Therefore the number of chest CT examinations can be expected to increase, especially for high-risk groups. These facts may result in a dramatic increase in the number of pulmonary nodules detected worldwide. In these circumstances, it is very important for clinicians to differentiate malignant from benign nodules in the least invasive manner and to make as specific and as accurate a diagnosis as possible.”

In this study, a total of 52 patients presenting 96 solitary lung nodules were included in the research. Of the pulmonary nodules, 15 were classified as benign with low biologic activity, 24 as benign with high activity and 57 as malignant.

Pulmonary arterial and systemic arterial perfusions were analyzed via a dual-input maximum slope method, and perfusion was analyzed by the single-input maximum slope method. Extraction fraction and blood volume (BV) were analyzed using the Patlak plot method. All data were compared by statistical analysis according to classification. Diagnostic capability of each method was determined by maximum standardized uptake value and variability of parameters across classifications, compared by receiver operating characteristic analyses. With the exception of extraction fraction and BV, all indexes showed marked differences between class. “Areas under the curve of total perfusion calculated using the dual-input method, pulmonary arterial perfusion calculated using the dual-input method and perfusion calculated using the single-input method were significantly larger than that of [maximum SUV],” wrote Ohno et al.

“Dynamic area-detector CT analyzed using the dual-input maximum slope method has better potential for the diagnosis of pulmonary nodules than dynamic area detector CT analyzed using other methods than PET/CT,” the authors wrote.

Accuracy of total perfusion was found to be 83 percent, significantly more than that of the other indexes. Pulmonary arterial perfusion accuracy was calculated as 72.9 percent, systemic arterial perfusion analyzed by dual-input method 69.8 percent, perfusion was found to be 66.7 percent accurate and maximum SUV was 60.4 percent.

 “Our results show that the newly developed dual-input maximum slope method for dynamic first-pass perfusion area-detector CT can show significant and reproducible differences among malignant nodules, benign nodules with anticipated low biologic activity, and benign nodules with anticipated high biologic activity,” the researchers wrote. “In this respect, it is as good as the single-input maximum slope method for dynamic first-pass perfusion area-detector CT and PET/CT, whereas the Patlak plot method for dynamic first-pass perfusion area-detector CT did not indicate any significant difference among the three nodule groups. In addition, total perfusion within nodules assessed from dynamic first-pass perfusion area-detector CT data with the dual-input maximum slope method could differentiate malignant from benign nodules and nodules requiring aggressive intervention and treatment from nodules requiring follow-up examination with sensitivity and accuracy as good as or better than perfusion within nodules assessed from the same area-detector CT data with the single-input maximum slope method and SUVmax."